halgir

I spent some years as a product manager. This might be a cynical take, but my relationship with AI-written code is largely the same as it was with human-written code.

I would research and explain what I wanted the product to do. We'd discuss technical trade-offs, drawbacks, and risks. Eventually, we'd ship something. I understood broadly how the infrastructure worked, but to a large extent I had to trust the quality of the code my colleagues were writing. Sometimes things broke. That's okay, we're only human.

I think I'm just more comfortable being held responsible for something I don't fully understand because I always have been. Maybe I'm delusional and the comparison won't hold. We'll see.

> Think of a problem that we saw coming in the future and we collectively solved. I can think of none.

My favorite counterexample is the ozone layer. When I was a kid, that was the Big Bad environmental concern. But we actually worked together on a global scale to fix it.

Broader climate change is a much bigger problem with stronger financial and political incentives, but in principle we've done it before.

> run-away climate change

We have one. But according to Down Detector's Down Detector's Down Detector's Down Detector, that's also down.

What's Updog?

It does. I eat small portions, rarely. My son has fortunately not expressed any interest in eating it, and I won't encourage him to.

I dislike Sea Shepherd as an organization, due to their distasteful methods (and personal bias, being a Faroese resident). But I spoke with several of their volunteers during one of their campaigns, and was pleased to realize that, as individuals, their hearts are mostly in the right place. Nearly all of them claimed to be vegan, which I feel does give you legitimate ethical grounds from which to criticize grindadráp.

However, if you don't oppose the general consumption of meat, I don't find the argument against grindadráp compelling. It yields more meat per killed animal than most, and the slaughter itself is arguably no less humane than most commercial meat production (not a high bar, I admit).

In terms of publicity, grindadráp suffers from being inherently more visible than commercial meat production. Personally, I think this is a positive thing. It confronts you with the fact that meat doesn't magically appear in a supermarket freezer - if you want to eat meat, then by definition a living animal has to die. The visibility of grindadráp has prompted conversations with my young son about where meat comes from, and the animal welfare consequences of eating it.

But who will the align the aligner of aligners? :(

Apropos mixing bitterants, it's quite common to apply a bitter nail varnish to help people stop biting their nails. Not an addictive substance, but an addictive behavior.

> How can you ensure that the exercise actually teaches the students anything in this case?

By participating in the exercise during class. Introducing the cases, facilitating group discussions, and providing academic input when bringing the class back together for a review. I'm not just saying "hey take a look at this or whatever".

> If you're teaching ethics in high school (which it sounds like you are)

Briefly and temporarily. I have no formal pedagogic background. Input appreciated.

> This may sound harsh, but to me it sounds like you've created a non-didactic, busywork exercise.

I may not have elaborated well enough on the context. I'm not creating slop in order to avoid doing work. I'm using the tools available to do more work faster - and sometimes coming across examples or cases that I realized I wouldn't have thought of myself. And, crucially, strictly supervising any and all work that the LLM produces.

If I had infinite time, then I'd happily spend it on meticulously handcrafting materials. But as this thread makes clear, that's a rare luxury in education.

There is a middle ground between artisanal powerpoint craftsmanship and AI slop.

I agree you shouldn't use LLMs to produce material wholesale, but I think it can be positively useful when used thoughtfully.

I recently taught a high school equivalent philosophy class, and wanted to design an exercise for my students to allocate a limited number of organs to recipients that were not directly comparable. I asked an LLM to generate recipient profiles for the students to choose between. First pass, the recipients all needed different organs, which kind of ruined the point of the dilemma! I told it so, and second pass was great.

Even with the extra handholding, the LLM made good materials faster than if I would have designed them manually. But if I had trusted it blindly, the materials would have been useless.

That sounds horrible. Thanks for the insight.